How to fill an empty sparse tensor?

I am initiating a sparse tensor using x = torch.sparse.FloatTensor(100,100,3). I want to fill it up later at different times. How can I do so? I am using this as a representation of a growing graph.

Doing x[1,1,:] = torch.Tensor([1,2,3]) throws RuntimeError: sparse tensors do not have strides.
Or just doing x[1] returns the same error.

A sparse tensor in pytorch is represented as a pair of dense tensors: a tensor of values and a 2D tensor of indices. sparse tensor don’t have strides, the directed indexing operation such as x[1] is not allow. torch.sparse module is currently experimental, maybe using dense tensor is preferred

torch.randn(2, 3).to_sparse()
tensor(indices=tensor([[0, 0, 0, 1, 1, 1],
                       [0, 1, 2, 0, 1, 2]]),
       values=tensor([ 0.5527, -0.7956,  0.7942,  0.6294,  0.9592,  0.3199]),
       size=(2, 3), nnz=6, layout=torch.sparse_coo)